{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "satisfied-antenna",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Using CellTypist for multi-label classification\n",
    "This notebook showcases the multi-label classification for scRNA-seq query data using either the built-in CellTypist models or the user-trained custom models."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "surprised-yellow",
   "metadata": {},
   "source": [
    "Only the main steps and key parameters are introduced in this notebook. Refer to detailed [Usage](https://github.com/Teichlab/celltypist#usage) if you want to learn more."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "after-allergy",
   "metadata": {},
   "source": [
    "## About multi-label cell type classification"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "thermal-spencer",
   "metadata": {},
   "source": [
    "An ideal CellTypist model is supposed to be trained from a reference atlas with a comprehensive cell type repertoire. For the built-in models, we have collected a large number of cell types; yet, the presence of unexpected (e.g., low-quality or novel cell types) and ambiguous cell states (e.g., doublets) in the query data is beyond the prediction that CellTypist can achieve with a 'find-a-best-match' mode. To overcome this, CellTypist provides the option of multi-label cell type classification, which assigns 0 (i.e., unassigned), 1, or >=2 cell type labels to each query cell."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "empirical-tiffany",
   "metadata": {},
   "source": [
    "## Install CellTypist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "painted-cleaning",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting celltypist\n",
      "  Using cached celltypist-1.2.0-py3-none-any.whl (5.3 MB)\n",
      "Requirement already satisfied: click>=7.1.2 in /opt/conda/lib/python3.8/site-packages (from celltypist) (7.1.2)\n",
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      "Requirement already satisfied: leidenalg>=0.8.3 in /opt/conda/lib/python3.8/site-packages (from celltypist) (0.8.3)\n",
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      "Requirement already satisfied: numpy>=1.19.0 in /opt/conda/lib/python3.8/site-packages (from celltypist) (1.20.1)\n",
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      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas>=1.0.5->celltypist) (1.15.0)\n",
      "Requirement already satisfied: chardet<5,>=3.0.2 in /opt/conda/lib/python3.8/site-packages (from requests>=2.23.0->celltypist) (4.0.0)\n",
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      "Requirement already satisfied: packaging in /opt/conda/lib/python3.8/site-packages (from scanpy>=1.7.0->celltypist) (20.9)\n",
      "Requirement already satisfied: scipy>=1.4 in /opt/conda/lib/python3.8/site-packages (from scanpy>=1.7.0->celltypist) (1.6.1)\n",
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      "Requirement already satisfied: h5py>=2.10.0 in /opt/conda/lib/python3.8/site-packages (from scanpy>=1.7.0->celltypist) (3.1.0)\n",
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      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=3.1.2->scanpy>=1.7.0->celltypist) (2.4.7)\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=3.1.2->scanpy>=1.7.0->celltypist) (0.10.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=3.1.2->scanpy>=1.7.0->celltypist) (1.3.1)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.8/site-packages (from matplotlib>=3.1.2->scanpy>=1.7.0->celltypist) (8.1.2)\n",
      "Requirement already satisfied: decorator>=4.3.0 in /opt/conda/lib/python3.8/site-packages (from networkx>=2.3->scanpy>=1.7.0->celltypist) (4.4.2)\n",
      "Requirement already satisfied: llvmlite<0.35,>=0.34.0.dev0 in /opt/conda/lib/python3.8/site-packages (from numba>=0.41.0->scanpy>=1.7.0->celltypist) (0.34.0)\n",
      "Requirement already satisfied: setuptools in /opt/conda/lib/python3.8/site-packages (from numba>=0.41.0->scanpy>=1.7.0->celltypist) (49.6.0.post20210108)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in /opt/conda/lib/python3.8/site-packages (from scikit-learn>=0.24.1->celltypist) (2.1.0)\n",
      "Requirement already satisfied: get-version>=2.0.4 in /opt/conda/lib/python3.8/site-packages (from legacy-api-wrap->scanpy>=1.7.0->celltypist) (2.1)\n",
      "Requirement already satisfied: stdlib-list in /opt/conda/lib/python3.8/site-packages (from sinfo->scanpy>=1.7.0->celltypist) (0.7.0)\n",
      "Requirement already satisfied: numexpr>=2.6.2 in /opt/conda/lib/python3.8/site-packages (from tables->scanpy>=1.7.0->celltypist) (2.7.3)\n",
      "Installing collected packages: celltypist\n",
      "Successfully installed celltypist-1.2.0\n"
     ]
    }
   ],
   "source": [
    "!pip install celltypist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "technical-subcommittee",
   "metadata": {},
   "outputs": [],
   "source": [
    "import scanpy as sc\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "conceptual-trust",
   "metadata": {},
   "outputs": [],
   "source": [
    "import celltypist\n",
    "from celltypist import models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "indirect-therapy",
   "metadata": {},
   "source": [
    "## Download a scRNA-seq dataset of 500 immune cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "geographic-concert",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f81e4d30255447c4b582e8bd983f1e9f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0.00/9.41M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata_500 = sc.read('celltypist_demo_folder/demo_500_cells.h5ad', backup_url = 'https://celltypist.cog.sanger.ac.uk/Notebook_demo_data/demo_500_cells.h5ad')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "thousand-product",
   "metadata": {
    "tags": []
   },
   "source": [
    "This dataset includes 500 cells and 18,950 genes collected from different studies, thereby showing the practical applicability of CellTypist."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "official-armenia",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(500, 18950)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_500.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "passive-arrest",
   "metadata": {
    "tags": []
   },
   "source": [
    "The expression matrix (`adata_500.X`) is pre-processed (and required) as log1p normalised expression to 10,000 counts per cell (this matrix can be alternatively stashed in `.raw.X`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "received-lucas",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "matrix([[10000.   ],\n",
       "        [10000.001],\n",
       "        [ 9999.999],\n",
       "        [10000.001],\n",
       "        [10000.003],\n",
       "        [ 9999.999],\n",
       "        [10000.   ],\n",
       "        [10000.002],\n",
       "        [10000.   ],\n",
       "        [ 9999.999]], dtype=float32)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_500.X.expm1().sum(axis = 1)[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "complicated-judgment",
   "metadata": {},
   "source": [
    "Some pre-assigned cell type labels are also in the data, which will be compared to the predicted labels from CellTypist later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "starting-fraction",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cell_type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cell1</th>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell2</th>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell3</th>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell4</th>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell5</th>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell496</th>\n",
       "      <td>Macro_pDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell497</th>\n",
       "      <td>Macro_pDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell498</th>\n",
       "      <td>Macro_pDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell499</th>\n",
       "      <td>Macro_pDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell500</th>\n",
       "      <td>Macro_pDC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            cell_type\n",
       "cell1    Plasma cells\n",
       "cell2    Plasma cells\n",
       "cell3    Plasma cells\n",
       "cell4    Plasma cells\n",
       "cell5    Plasma cells\n",
       "...               ...\n",
       "cell496     Macro_pDC\n",
       "cell497     Macro_pDC\n",
       "cell498     Macro_pDC\n",
       "cell499     Macro_pDC\n",
       "cell500     Macro_pDC\n",
       "\n",
       "[500 rows x 1 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata_500.obs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fresh-truck",
   "metadata": {},
   "source": [
    "Among the 12 cell types in this data, 10 are shared with the CellTypist built-in models. For the remaining two, `Microglia` is a novel cell type not covered by CellTypist (currently our models do not involve the brain), and `Macro_pDC` is a cell type *in silico* generated by blending the expression of macrophages with plasmacytoid dendritic cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "armed-guess",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.dotplot(adata_500, ['CX3CR1', 'C1QC', 'LILRA4'], groupby = 'cell_type', swap_axes = True, standard_scale = 'var', figsize = [12, 4])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "occasional-suffering",
   "metadata": {},
   "source": [
    "## Inspect the CellTypist built-in models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "rocky-violence",
   "metadata": {},
   "source": [
    "Download the latest CellTypist models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "chemical-banks",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "📜 Retrieving model list from server https://celltypist.cog.sanger.ac.uk/models/models.json\n",
      "📚 Total models in list: 12\n",
      "📂 Storing models in /home/jovyan/.celltypist/data/models\n",
      "💾 Downloading model [1/12]: Immune_All_Low.pkl\n",
      "💾 Downloading model [2/12]: Immune_All_High.pkl\n",
      "💾 Downloading model [3/12]: Adult_Mouse_Gut.pkl\n",
      "💾 Downloading model [4/12]: COVID19_Immune_Landscape.pkl\n",
      "💾 Downloading model [5/12]: Cells_Fetal_Lung.pkl\n",
      "💾 Downloading model [6/12]: Cells_Intestinal_Tract.pkl\n",
      "💾 Downloading model [7/12]: Cells_Lung_Airway.pkl\n",
      "💾 Downloading model [8/12]: Developing_Mouse_Brain.pkl\n",
      "💾 Downloading model [9/12]: Healthy_COVID19_PBMC.pkl\n",
      "💾 Downloading model [10/12]: Human_Lung_Atlas.pkl\n",
      "💾 Downloading model [11/12]: Nuclei_Lung_Airway.pkl\n",
      "💾 Downloading model [12/12]: Pan_Fetal_Human.pkl\n"
     ]
    }
   ],
   "source": [
    "# Enabling `force_update = True` will overwrite existing (old) models.\n",
    "models.download_models(force_update = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "moral-reserve",
   "metadata": {},
   "source": [
    "All models are stored in `models.models_path`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "adult-premises",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/jovyan/.celltypist/data/models'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models.models_path"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "falling-token",
   "metadata": {},
   "source": [
    "Get an overview of the models and what they represent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "relative-interaction",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "👉 Detailed model information can be found at `https://www.celltypist.org/models`\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>model</th>\n",
       "      <th>description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Immune_All_Low.pkl</td>\n",
       "      <td>immune sub-populations combined from 20 tissue...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Immune_All_High.pkl</td>\n",
       "      <td>immune populations combined from 20 tissues of...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Adult_Mouse_Gut.pkl</td>\n",
       "      <td>cell types in the adult mouse gut combined fro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>COVID19_Immune_Landscape.pkl</td>\n",
       "      <td>immune subtypes from lung and blood of COVID-1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Cells_Fetal_Lung.pkl</td>\n",
       "      <td>cell types from human embryonic and fetal lungs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Cells_Intestinal_Tract.pkl</td>\n",
       "      <td>intestinal cells from fetal, pediatric and adu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Cells_Lung_Airway.pkl</td>\n",
       "      <td>cell populations from scRNA-seq of five locati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Developing_Mouse_Brain.pkl</td>\n",
       "      <td>cell types from the embryonic mouse brain betw...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Healthy_COVID19_PBMC.pkl</td>\n",
       "      <td>peripheral blood mononuclear cell types from h...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Human_Lung_Atlas.pkl</td>\n",
       "      <td>integrated Human Lung Cell Atlas (HLCA) combin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Nuclei_Lung_Airway.pkl</td>\n",
       "      <td>cell populations from snRNA-seq of five locati...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Pan_Fetal_Human.pkl</td>\n",
       "      <td>stromal and immune populations from the human ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           model  \\\n",
       "0             Immune_All_Low.pkl   \n",
       "1            Immune_All_High.pkl   \n",
       "2            Adult_Mouse_Gut.pkl   \n",
       "3   COVID19_Immune_Landscape.pkl   \n",
       "4           Cells_Fetal_Lung.pkl   \n",
       "5     Cells_Intestinal_Tract.pkl   \n",
       "6          Cells_Lung_Airway.pkl   \n",
       "7     Developing_Mouse_Brain.pkl   \n",
       "8       Healthy_COVID19_PBMC.pkl   \n",
       "9           Human_Lung_Atlas.pkl   \n",
       "10        Nuclei_Lung_Airway.pkl   \n",
       "11           Pan_Fetal_Human.pkl   \n",
       "\n",
       "                                          description  \n",
       "0   immune sub-populations combined from 20 tissue...  \n",
       "1   immune populations combined from 20 tissues of...  \n",
       "2   cell types in the adult mouse gut combined fro...  \n",
       "3   immune subtypes from lung and blood of COVID-1...  \n",
       "4     cell types from human embryonic and fetal lungs  \n",
       "5   intestinal cells from fetal, pediatric and adu...  \n",
       "6   cell populations from scRNA-seq of five locati...  \n",
       "7   cell types from the embryonic mouse brain betw...  \n",
       "8   peripheral blood mononuclear cell types from h...  \n",
       "9   integrated Human Lung Cell Atlas (HLCA) combin...  \n",
       "10  cell populations from snRNA-seq of five locati...  \n",
       "11  stromal and immune populations from the human ...  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "models.models_description()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "precious-things",
   "metadata": {},
   "source": [
    "Choose the model you want to employ, for example, the model with all tissues combined containing low-hierarchy (high-resolution) immune cell types/subtypes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "emotional-shift",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Indeed, the `model` argument defaults to `Immune_All_Low.pkl`.\n",
    "model = models.Model.load(model = 'Immune_All_Low.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "lesser-grass",
   "metadata": {},
   "source": [
    "Show the model meta information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "global-thermal",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CellTypist model with 90 cell types and 5212 features\n",
       "    date: 2022-04-04 23:51:15.159293\n",
       "    details: immune sub-populations combined from 20 tissues of 19 studies\n",
       "    source: https://doi.org/10.1126/science.abl5197\n",
       "    version: v2\n",
       "    cell types: B cells, CD16+ NK cells, ..., pDC precursor\n",
       "    features: A1BG, A2M, ..., ZYX"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "continuous-malaysia",
   "metadata": {},
   "source": [
    "This model contains 90 cell states."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "adaptive-compiler",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['B cells', 'CD16+ NK cells', 'CD16- NK cells', 'CD8a/a',\n",
       "       'CD8a/b(entry)', 'CMP', 'Classical monocytes', 'Cycling B cells',\n",
       "       'Cycling DCs', 'Cycling NK cells', 'Cycling T cells',\n",
       "       'Cycling gamma-delta T cells', 'Cycling monocytes', 'DC',\n",
       "       'DC precursor', 'DC1', 'DC2', 'DC3', 'Double-negative thymocytes',\n",
       "       'Double-positive thymocytes', 'ELP', 'ETP', 'Early MK',\n",
       "       'Early erythroid', 'Early lymphoid/T lymphoid',\n",
       "       'Endothelial cells', 'Epithelial cells', 'Erythrocytes',\n",
       "       'Fibroblasts', 'Follicular B cells', 'Follicular helper T cells',\n",
       "       'GMP', 'Germinal center B cells', 'Granulocytes', 'HSC/MPP',\n",
       "       'Hofbauer cells', 'ILC', 'ILC precursor', 'ILC1', 'ILC2', 'ILC3',\n",
       "       'Kidney-resident macrophages', 'Kupffer cells',\n",
       "       'Large pre-B cells', 'Late erythroid', 'MAIT cells', 'MEMP', 'MNP',\n",
       "       'Macrophages', 'Mast cells', 'Megakaryocyte precursor',\n",
       "       'Megakaryocyte-erythroid-mast cell progenitor',\n",
       "       'Megakaryocytes/platelets', 'Memory B cells',\n",
       "       'Memory CD4+ cytotoxic T cells', 'Mid erythroid', 'Migratory DCs',\n",
       "       'Mono-mac', 'Monocyte precursor', 'Monocytes', 'Myelocytes',\n",
       "       'NK cells', 'NKT cells', 'Naive B cells',\n",
       "       'Neutrophil-myeloid progenitor', 'Neutrophils',\n",
       "       'Non-classical monocytes', 'Plasma cells', 'Pre-pro-B cells',\n",
       "       'Pro-B cells', 'Promyelocytes', 'Regulatory T cells',\n",
       "       'Small pre-B cells', 'T(agonist)', 'Tcm/Naive cytotoxic T cells',\n",
       "       'Tcm/Naive helper T cells', 'Tem/Effector helper T cells',\n",
       "       'Tem/Effector helper T cells PD1+', 'Tem/Temra cytotoxic T cells',\n",
       "       'Tem/Trm cytotoxic T cells', 'Transitional B cells',\n",
       "       'Transitional DC', 'Transitional NK', 'Treg(diff)',\n",
       "       'Trm cytotoxic T cells', 'Type 1 helper T cells',\n",
       "       'Type 17 helper T cells', 'gamma-delta T cells', 'pDC',\n",
       "       'pDC precursor'], dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.cell_types"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "accessible-stadium",
   "metadata": {},
   "source": [
    "Note that all built-in models are continuously being updated. Thus following the same procedure below, you may produce a different result when using a older or newer model."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "peaceful-synthesis",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Single-label classification by finding the best match in the model\n",
    "In this section, we show the procedure of finding the most likely cell type labels from built-in models for the query dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sized-slide",
   "metadata": {
    "tags": []
   },
   "source": [
    "We use the default mode (`mode = 'best match'`) in [celltypist.annotate](https://celltypist.readthedocs.io/en/latest/celltypist.annotate.html) to transfer cell type labels from the model to the query dataset. With this mode on, each query cell is predicted into the cell type with the largest score/probability among all possible cell types in the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "wound-stanford",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "🔬 Input data has 500 cells and 18950 genes\n",
      "🔗 Matching reference genes in the model\n",
      "🧬 4715 features used for prediction\n",
      "⚖️ Scaling input data\n",
      "🖋️ Predicting labels\n",
      "✅ Prediction done!\n",
      "👀 Can not detect a neighborhood graph, will construct one before the over-clustering\n",
      "⛓️ Over-clustering input data with resolution set to 5\n",
      "🗳️ Majority voting the predictions\n",
      "✅ Majority voting done!\n"
     ]
    }
   ],
   "source": [
    "# Not run; predict cell identities using this loaded model.\n",
    "#predictions = celltypist.annotate(adata_500, model = model, majority_voting = True, mode = 'best match')\n",
    "# Alternatively, just specify the model name (recommended as this ensures the model is intact every time it is loaded).\n",
    "predictions = celltypist.annotate(adata_500, model = 'Immune_All_Low.pkl', majority_voting = True, mode = 'best match')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "under-arthritis",
   "metadata": {},
   "source": [
    "By default (`majority_voting = False`), CellTypist will infer the identity of each query cell independently. This leads to raw predicted cell type labels, and usually finishes within seconds or minutes depending on the size of the query data. You can also turn on the majority-voting classifier (`majority_voting = True`), which refines cell identities within local subclusters after an over-clustering approach at the cost of increased runtime."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "geographic-dividend",
   "metadata": {
    "tags": []
   },
   "source": [
    "The results include both predicted cell type labels (`predicted_labels`), over-clustering result (`over_clustering`), and predicted labels after majority voting in local subclusters (`majority_voting`). Note in the `predicted_labels`, each query cell gets its inferred label by choosing the most probable cell type among all possible cell types in the given model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "extended-diary",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>predicted_labels</th>\n",
       "      <th>over_clustering</th>\n",
       "      <th>majority_voting</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cell1</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>13</td>\n",
       "      <td>Follicular B cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell2</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>6</td>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell3</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>12</td>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell4</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>6</td>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell5</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>6</td>\n",
       "      <td>Plasma cells</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell496</th>\n",
       "      <td>pDC</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell497</th>\n",
       "      <td>Macrophages</td>\n",
       "      <td>18</td>\n",
       "      <td>pDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell498</th>\n",
       "      <td>Macrophages</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell499</th>\n",
       "      <td>Macrophages</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell500</th>\n",
       "      <td>pDC</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        predicted_labels over_clustering     majority_voting\n",
       "cell1       Plasma cells              13  Follicular B cells\n",
       "cell2       Plasma cells               6        Plasma cells\n",
       "cell3       Plasma cells              12        Plasma cells\n",
       "cell4       Plasma cells               6        Plasma cells\n",
       "cell5       Plasma cells               6        Plasma cells\n",
       "...                  ...             ...                 ...\n",
       "cell496              pDC               9         Macrophages\n",
       "cell497      Macrophages              18                 pDC\n",
       "cell498      Macrophages               9         Macrophages\n",
       "cell499      Macrophages               9         Macrophages\n",
       "cell500              pDC               9         Macrophages\n",
       "\n",
       "[500 rows x 3 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions.predicted_labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "adaptive-surrey",
   "metadata": {},
   "source": [
    "Transform the prediction result into an `AnnData`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "quarterly-phrase",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get an `AnnData` with predicted labels embedded into the cell metadata columns.\n",
    "adata = predictions.to_adata()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "common-accounting",
   "metadata": {},
   "source": [
    "Compared to `adata_500`, the new `adata` has additional prediction information in `adata.obs` (`predicted_labels`, `over_clustering`, `majority_voting` and `conf_score`). Of note, all these columns can be prefixed with a specific string by setting `prefix` in [to_adata](https://celltypist.readthedocs.io/en/latest/celltypist.classifier.AnnotationResult.html#celltypist.classifier.AnnotationResult.to_adata)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "turned-cedar",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cell_type</th>\n",
       "      <th>predicted_labels</th>\n",
       "      <th>over_clustering</th>\n",
       "      <th>majority_voting</th>\n",
       "      <th>conf_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cell1</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>13</td>\n",
       "      <td>Follicular B cells</td>\n",
       "      <td>0.996313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell2</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>6</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>0.999478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell3</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>12</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>0.999957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell4</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>6</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>0.996070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell5</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>6</td>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>0.998888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell496</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>pDC</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>0.187152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell497</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>18</td>\n",
       "      <td>pDC</td>\n",
       "      <td>0.849831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell498</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>0.809677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell499</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>0.937306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell500</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>pDC</td>\n",
       "      <td>9</td>\n",
       "      <td>Macrophages</td>\n",
       "      <td>0.612069</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            cell_type predicted_labels over_clustering     majority_voting  \\\n",
       "cell1    Plasma cells     Plasma cells              13  Follicular B cells   \n",
       "cell2    Plasma cells     Plasma cells               6        Plasma cells   \n",
       "cell3    Plasma cells     Plasma cells              12        Plasma cells   \n",
       "cell4    Plasma cells     Plasma cells               6        Plasma cells   \n",
       "cell5    Plasma cells     Plasma cells               6        Plasma cells   \n",
       "...               ...              ...             ...                 ...   \n",
       "cell496     Macro_pDC              pDC               9         Macrophages   \n",
       "cell497     Macro_pDC      Macrophages              18                 pDC   \n",
       "cell498     Macro_pDC      Macrophages               9         Macrophages   \n",
       "cell499     Macro_pDC      Macrophages               9         Macrophages   \n",
       "cell500     Macro_pDC              pDC               9         Macrophages   \n",
       "\n",
       "         conf_score  \n",
       "cell1      0.996313  \n",
       "cell2      0.999478  \n",
       "cell3      0.999957  \n",
       "cell4      0.996070  \n",
       "cell5      0.998888  \n",
       "...             ...  \n",
       "cell496    0.187152  \n",
       "cell497    0.849831  \n",
       "cell498    0.809677  \n",
       "cell499    0.937306  \n",
       "cell500    0.612069  \n",
       "\n",
       "[500 rows x 5 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata.obs"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "defensive-advertiser",
   "metadata": {},
   "source": [
    "In addition to this meta information added, the neighborhood graph constructed during over-clustering is also stored in the `adata` \n",
    "(If a pre-calculated neighborhood graph is already present in the `AnnData`, this graph construction step will be skipped).  \n",
    "This graph can be used to derive the cell embeddings, such as the UMAP coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "numerous-determination",
   "metadata": {},
   "outputs": [],
   "source": [
    "# If the UMAP or any cell embeddings are already available in the `AnnData`, skip this command.\n",
    "sc.tl.umap(adata)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "wound-summer",
   "metadata": {},
   "source": [
    "Visualise the prediction results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "severe-surfing",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 989.28x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(adata, color = ['cell_type', 'majority_voting'], legend_loc = 'on data')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "hollow-failing",
   "metadata": {
    "tags": []
   },
   "source": [
    "As the images show, with the default mode, `Microglia` is predicted as a mixture of cell types, and `Macro_pDC` is mostly predicted as `Macrophages`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dense-pickup",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>majority_voting</th>\n",
       "      <th>DC</th>\n",
       "      <th>DC1</th>\n",
       "      <th>Endothelial cells</th>\n",
       "      <th>Follicular B cells</th>\n",
       "      <th>Kupffer cells</th>\n",
       "      <th>Macrophages</th>\n",
       "      <th>Mast cells</th>\n",
       "      <th>Naive B cells</th>\n",
       "      <th>Neutrophil-myeloid progenitor</th>\n",
       "      <th>Plasma cells</th>\n",
       "      <th>gamma-delta T cells</th>\n",
       "      <th>pDC</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell_type</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Microglia</th>\n",
       "      <td>2</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Macro_pDC</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "majority_voting  DC  DC1  Endothelial cells  Follicular B cells  \\\n",
       "cell_type                                                         \n",
       "Microglia         2   14                  1                   0   \n",
       "Macro_pDC         0    0                  0                   0   \n",
       "\n",
       "majority_voting  Kupffer cells  Macrophages  Mast cells  Naive B cells  \\\n",
       "cell_type                                                                \n",
       "Microglia                    0           31           0              6   \n",
       "Macro_pDC                    0           30           0              0   \n",
       "\n",
       "majority_voting  Neutrophil-myeloid progenitor  Plasma cells  \\\n",
       "cell_type                                                      \n",
       "Microglia                                    1             0   \n",
       "Macro_pDC                                    0             0   \n",
       "\n",
       "majority_voting  gamma-delta T cells  pDC  \n",
       "cell_type                                  \n",
       "Microglia                          0    5  \n",
       "Macro_pDC                          0   10  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(adata.obs.cell_type, adata.obs.majority_voting).loc[['Microglia','Macro_pDC']]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "light-shopping",
   "metadata": {},
   "source": [
    "Actually, you may not need to explicitly convert `predictions` output by `celltypist.annotate` into an `AnnData` as above. A more useful way is to use the visualisation function [celltypist.dotplot](https://celltypist.readthedocs.io/en/latest/celltypist.dotplot.html), which quantitatively compares the CellTypist prediction result (e.g. `predicted_labels` here) with the cell types pre-defined in the `AnnData` (here `cell_type`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "chief-craft",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 427.68x676.8 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "celltypist.dotplot(predictions, use_as_reference = 'cell_type', use_as_prediction = 'predicted_labels')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "geographic-davis",
   "metadata": {},
   "source": [
    "For each pre-defined cell type (each column from the dot plot), this plot shows how it can be 'decomposed' into different cell types predicted by CellTypist (rows). You can also change the value of `use_as_prediction` to `majority_voting` to compare the majority-voting result with the pre-defined cell types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "underlying-infection",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 427.68x374.4 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "celltypist.dotplot(predictions, use_as_reference = 'cell_type', use_as_prediction = 'majority_voting')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "searching-window",
   "metadata": {},
   "source": [
    "## Multi-label classification by utilising a probability threshold\n",
    "In this section, we show the procedure of transferring multiple cell type labels from built-in models to the query dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unusual-canberra",
   "metadata": {
    "tags": []
   },
   "source": [
    "All cell types from the CellTypist models are trained in an one-vs-rest fashion, resulting in independent probability estimates that can be compared across cell types. Probabilities are transformed from the decision scores by the sigmoid function, and are kept as is without summing up to one for each query cell. Through this, a probability threshold (default to 0.5, `p_thres = 0.5`) can be used to determine the cell type(s) assigned to a given cell."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "residential-catalog",
   "metadata": {},
   "source": [
    "Turn on the multi-label classification by setting the `mode = 'prob match'` argument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "visible-charleston",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "🔬 Input data has 500 cells and 18950 genes\n",
      "🔗 Matching reference genes in the model\n",
      "🧬 4715 features used for prediction\n",
      "⚖️ Scaling input data\n",
      "🖋️ Predicting labels\n",
      "✅ Prediction done!\n",
      "👀 Detected a neighborhood graph in the input object, will run over-clustering on the basis of it\n",
      "⛓️ Over-clustering input data with resolution set to 5\n",
      "🗳️ Majority voting the predictions\n",
      "✅ Majority voting done!\n"
     ]
    }
   ],
   "source": [
    "# `p_thres` defaults to 0.5.\n",
    "predictions = celltypist.annotate(adata_500, model = 'Immune_All_Low.pkl', majority_voting = True, mode = 'prob match', p_thres = 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "resistant-horizon",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "adata = predictions.to_adata()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "subtle-effect",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "sc.tl.umap(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "orange-istanbul",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 989.28x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(adata, color = ['cell_type', 'majority_voting'], legend_loc = 'on data')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "homeless-count",
   "metadata": {
    "tags": []
   },
   "source": [
    "With the mode of probabilistic match, `Microglia` is predicted as `Unassigned`, and `Macro_pDC` is predicted as `Macrophages|pDC` (which follows the naming scheme of `celltype1|celltyp2`)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "tribal-patrick",
   "metadata": {
    "tags": []
   },
   "source": [
    "The probability estimates can be inserted into the adata as well by setting `insert_prob = True` in the `to_adata` function. After the insertion, multiple columns will show up in the cell metadata, with each column's name being a cell type name (no `prefix` by default) representing probabilities of this cell type distributed across the query cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "anonymous-slope",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cell_type</th>\n",
       "      <th>Plasma cells</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>cell1</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>9.963127e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell2</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>9.994784e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell3</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>9.999570e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell4</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>9.960702e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell5</th>\n",
       "      <td>Plasma cells</td>\n",
       "      <td>9.988881e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell496</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>4.877905e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell497</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>5.033182e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell498</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>3.668227e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell499</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>5.105727e-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cell500</th>\n",
       "      <td>Macro_pDC</td>\n",
       "      <td>6.045739e-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>500 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            cell_type  Plasma cells\n",
       "cell1    Plasma cells  9.963127e-01\n",
       "cell2    Plasma cells  9.994784e-01\n",
       "cell3    Plasma cells  9.999570e-01\n",
       "cell4    Plasma cells  9.960702e-01\n",
       "cell5    Plasma cells  9.988881e-01\n",
       "...               ...           ...\n",
       "cell496     Macro_pDC  4.877905e-06\n",
       "cell497     Macro_pDC  5.033182e-07\n",
       "cell498     Macro_pDC  3.668227e-06\n",
       "cell499     Macro_pDC  5.105727e-06\n",
       "cell500     Macro_pDC  6.045739e-06\n",
       "\n",
       "[500 rows x 2 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata = predictions.to_adata(insert_prob = True)\n",
    "adata.obs[['cell_type', 'Plasma cells']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "joint-blink",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1483.92x288 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(adata, color = ['cell_type', 'Macrophages', 'pDC'], vmin = 0, vmax = 1, legend_loc = 'on data')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "diverse-architecture",
   "metadata": {},
   "source": [
    "Examination of probability distributions of `Macrophages` and `pDC` shows the co-existence of their signatures in the doublet cluster `Macro_pDC`, as well as noticeable `Macrophages` scores in the `Microglia` cluster. Thus even CellTypist assigns the `Microglia` as `Unassigned`, the probability scores still indicate their possible transcriptomic similarity with `Macrophages`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "continued-piano",
   "metadata": {},
   "source": [
    "## Multi-label classification using a custom model\n",
    "In this section, we show the procedure of generating a custom model and transferring multiple labels from the model to the query data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "applied-notion",
   "metadata": {
    "tags": []
   },
   "source": [
    "Download a dataset of 2,000 immune cells as the training set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "convinced-peoples",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "09c4440f606b4e72937873b433bda4a3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0.00/34.1M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata_2000 = sc.read('celltypist_demo_folder/demo_2000_cells.h5ad', backup_url = 'https://celltypist.cog.sanger.ac.uk/Notebook_demo_data/demo_2000_cells.h5ad')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "modular-jumping",
   "metadata": {},
   "source": [
    "Use previously downloaded scRNA-seq dataset of 500 immune cells as a query."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bright-cincinnati",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata_500 = sc.read('celltypist_demo_folder/demo_500_cells.h5ad', backup_url = 'https://celltypist.cog.sanger.ac.uk/Notebook_demo_data/demo_500_cells.h5ad')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vertical-slovenia",
   "metadata": {
    "tags": []
   },
   "source": [
    "Derive a custom model by training the data using the [celltypist.train](https://celltypist.readthedocs.io/en/latest/celltypist.train.html) function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "silent-japan",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "🍳 Preparing data before training\n",
      "✂️ 2749 non-expressed genes are filtered out\n",
      "⚖️ Scaling input data\n",
      "🏋️ Training data using SGD logistic regression\n",
      "🔎 Selecting features\n",
      "🧬 2619 features are selected\n",
      "🏋️ Starting the second round of training\n",
      "🏋️ Training data using logistic regression\n",
      "✅ Model training done!\n"
     ]
    }
   ],
   "source": [
    "# The `cell_type` in `adata_2000.obs` will be used as cell type labels for training.\n",
    "new_model = celltypist.train(adata_2000, labels = 'cell_type', n_jobs = 10, feature_selection = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "israeli-eugene",
   "metadata": {},
   "source": [
    "Refer to the function [celltypist.train](https://celltypist.readthedocs.io/en/latest/celltypist.train.html) for what each parameter means, and to the [usage](https://github.com/Teichlab/celltypist#usage) for details of model training."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "impaired-boundary",
   "metadata": {},
   "source": [
    "This custom model can be manipulated as with other CellTypist built-in models. First, save this model locally."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ongoing-disposal",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the model.\n",
    "new_model.write('celltypist_demo_folder/model_from_immune2000.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dress-qatar",
   "metadata": {
    "tags": []
   },
   "source": [
    "You can load this model by `models.Model.load`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "regular-poland",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_model = models.Model.load('celltypist_demo_folder/model_from_immune2000.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "american-perry",
   "metadata": {},
   "source": [
    "Next, we use this model to predict the query dataset of 500 immune cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "dirty-galaxy",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "🔬 Input data has 500 cells and 18950 genes\n",
      "🔗 Matching reference genes in the model\n",
      "🧬 2619 features used for prediction\n",
      "⚖️ Scaling input data\n",
      "🖋️ Predicting labels\n",
      "✅ Prediction done!\n",
      "👀 Can not detect a neighborhood graph, will construct one before the over-clustering\n",
      "⛓️ Over-clustering input data with resolution set to 5\n",
      "🗳️ Majority voting the predictions\n",
      "✅ Majority voting done!\n"
     ]
    }
   ],
   "source": [
    "# Not run; predict the identity of each input cell with the new model.\n",
    "#predictions = celltypist.annotate(adata_500, model = new_model, majority_voting = True, mode = 'prob match', p_thres = 0.5)\n",
    "# Alternatively, just specify the model path (recommended as this ensures the model is intact every time it is loaded).\n",
    "predictions = celltypist.annotate(adata_500, model = 'celltypist_demo_folder/model_from_immune2000.pkl', majority_voting = True, mode = 'prob match', p_thres = 0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "acquired-nudist",
   "metadata": {},
   "outputs": [],
   "source": [
    "adata = predictions.to_adata(insert_prob = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "headed-rings",
   "metadata": {},
   "outputs": [],
   "source": [
    "sc.tl.umap(adata)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "varying-anatomy",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 989.28x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sc.pl.umap(adata, color = ['cell_type', 'majority_voting'], legend_loc = 'on data')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "immune-mercy",
   "metadata": {},
   "source": [
    "Again, `Microglia` is predicted as `Unassigned`, and `Macro_pDC` is predicted as `Macrophages|pDC`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "massive-wages",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Macro_pDC'}>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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99cHvBTi0z3+vmVl3XKitLT2x9CzuOavvC+qoUy/p899ptiHmz5/PjBkzWLp0KWPGjGH69OlMnjy57FjWh1yozcwqav78+UyfPp05c+YwYcIEFi1axJQpUwBcrNuIr1GbmVXUjBkzmDNnDhMnTmTIkCFMnDiROXPmMGPGjLKjWR9yoTYzq6ilS5cyYcKETvsmTJjA0qVLS0pkG4MLtZlZRY0ZM4ZFixZ12rdo0SLGjBlTUiLbGFyozcwqavr06UyZMoWFCxeyatUqFi5cyJQpU5g+fXrZ0awPuTOZmVlF1TqMTZs2bU2v7xkzZrgjWZtxoTYzq7DJkye7MLc5N32bmZllzIXazMwsYy7UZmZmGXOhNjMzy5gLtZmZWcZcqM3MzDLmQm1mZpYxF2ozM7OMuVCbmZllzIXazMwsYy7UZmZmGXOhNjMzy5gLtZlZhc2fP59x48YxaNAgxo0bx/z588uOZH3Mq2eZmVXU/PnzmT59OnPmzGHChAksWrSIKVOmAHhFrTbiM2ozs4qaMWMGRxxxBNOmTWPYsGFMmzaNI444ghkzZpQdzfqQz6itbY069ZI+/51bbjqkz3+n2fq6/fbbWb58OXPnzl1zRv3BD36Qe++9t+xo1odcqK0t3XPWoS3fd9Spl/Tq/ma52GSTTZg2bRoTJ04EYOLEiUybNo3PfOYzJSezvjQgmr7d2cLM2tHKlSs566yzGD16NB0dHYwePZqzzjqLlStXlh3N+lDbF+r58+dz4oknsnz5cgCWL1/OiSee6GJtZpW3ww47sGrVKgAkAbBq1Sp22GGHMmNZH2v7Qn3yySczePBg5s6dy4oVK5g7dy6DBw/m5JNPLjuamdkGW7lyJQ888ACrV6/mgQce8Nl0G2r7Qn3//fdz9NFHd+oVefTRR3P//feXHa0pN9ebWU8eeOABnnrqqTVn1atWreKpp57igQceKDlZ+5k0aRIdHR1IoqOjg0mTJvXb3277Qg0wc+ZMlixZwurVq1myZAkzZ84sO1JT9c31EeHmequsMj/c1leVviRHBJLYbrvtANhuu+2QRESUnKy9TJo0iQULFqy5vCCJBQsW9NvreUAU6pUrV3Z6gnNvGjr55JPXybhy5Uo311ullP3htj5qE4jMmjWLFStWMGvWLKZPn551sYb0mbF8+XJ/RmwkCxYsAGD16tWd/q3t3+gioscb8CbgTmAZcGqD4wK+Xhy/Bdi71cc2uu2zzz7RV4AAYquttur0b/pPzxMQ2223XVx55ZWxcuXKuPLKK2O77bbLOrOkNc8rEJLKjtSynU75ZdkRWnLwwQeveZ4lxcEHH1x2pKbqXw9db7kaO3ZsDBs2rFPWYcOGxdixY8uO1hAQBx54YIwdOzY6Ojpi7NixceCBB2b9HEdE7LHHHp2e4z322KPsSE3Vch533HHx6KOPxnHHHdfnr2VgcXRXg7s7EGsL7SDgz8BLgE2Am4Hdu9znzcCvioL9auAPrT620a2vC/UBBxzQ6YV8wAEHZP1CBuLss8/utO/ss8/ONnOteAwbNiyuvfbaNR90VSnWVSjUBx98cMMPipyLdX98uPW1Wr5Ro0bFsmXLYtSoUVlnBqKjoyNmzpwZy5cvj5kzZ0ZHR0e2eSPWFunDDjssHn744TjssMOyL9ZA7Lbbbp327bbbblkV6v2Ay+q2Pw18ust9vgNMrtu+E3hRK49tdOvrQr3ZZpt1OjvdbLPNsnshNzv7yP2MpFak69WKdRVUoVBLiuOOO67TvuOOOy7rL0P98eHW12qtWfVybM2q+ufFYYcd1mlfrVjnpL+f42aFWtFDpwNJ7wLeFBEfKrbfD7wqIo6vu88vgbMiYlGxfQVwCjCqp8fW/Y6pwFSAkSNH7tPqFHh7nLdHS/dbH7cedWuf/86NmReql3lj5O1O7Vppq3p6b/Qlvy4621ivi6pl9uuis6rlhdYzS7ohIsY3PNhdBa/dgHcD363bfj8wq8t9LgEm1G1fAezTymMb3fryjPr4449v+O3n+OOP77O/0dfmzZsXI0aMiFGjRkVHR0eMGjUqRowYEfPmzSs7WkNU/Iy6Cqp6Rt3dLVdAbLPNNp0ulW2zzTZZZ543b16nvLl+TtRQkTPqerVLT7XLCrV/+/LSEwO56TsiFeuhQ4cGEEOHDs26SNdU6c1X9WvUVVDFa9T98eHW14YPH97wGvXw4cPLjtY2qniNOmLjd+bc0EI9GLgbGM3aDmFju9znUDp3Jruu1cc2uvV1obaNr8q9vquiar2+I6qZuVasazcX6b5XtV7f/aFZoe5x9ayIeFbS8cBlpF7ccyNiiaRji+OzgUtJPb+XAU8BxzR7bE9/06qnNq7QNp7LLrus7Ai9VsXMTz75ZNkR2t4tt9xSdoRK6bEzWRnGjx8fixcvLjuGmZlZv2jWmWxAzExmZmZWVS7UZmZmGXOhNjMzy5gLtZmZWcay7Ewm6WGgtanJemdb4B8b4fduTFXLXLW8UL3MVcsLztwfqpYXnLneThExotGBLAv1xiJpcXe96nJVtcxVywvVy1y1vODM/aFqecGZW+WmbzMzs4y5UJuZmWVsoBXqc8oOsB6qlrlqeaF6mauWF5y5P1QtLzhzSwbUNWozM7OqGWhn1GZmZpXiQm1mZpYxF2rrM5K2krRn2TksL5I6JG1Rdo5mJA2S9PGyc6yvKr73qpi5LC7UmZE0XFJH8fOukg6TNKTsXN2R9BtJW0jamrTe+LmSvlp2rmaq9hx3VZHCN694XQwHbgfulPSpsnN1JyKeAw4vO0dvVPS9V7nMORiQhVrSZmVnaOJqYJikHYArSGt7f6/URM1tGRGPA+8Azo2IfYA3lpypJ1V7jitX+IDdi9fF20jr1Y8E3l9qop79TtI3JL1W0t61W9mhmqjie69SmSW9VNJrGux/raSd+yvHgCzUpA+6XCkiniK9kGdFxNuB3UvO1MxgSS8C3gP8suwwLaracwzVK3xDilaKtwE/j4hVQO5DTPYHxgJnADOL21dKTdRcFd97Vcv8n8ATDfY/XRzrF4P76w/1N0kndXcIyPmMWpL2A44EphT7cv7/dAZwGbAoIq6X9BLgrpIz9aRqzzF0LnzfiIhVknIufN8B7iE1b14taSfg8VIT9SAiJpadoZeq+N6rWuZREXFL150RsVjSqP4K0bbjqCWtAP4DeLbB4Y9HxPP7N1FrJL0O+ATwu4j4cvFC/lhEnFBytLZRxedY0gnAKaTCdyjpjPoHEfHaUoP1gqTBEdHo/ZgFSVsCpwEHFLuuAs6IiMfKS2VlkrQsIl7a22N9nqONC/U1wLSIuKHBsfsiYscSYrUNSbNo0pSZc9FrFzkWviYtWQBERLYdhyT9GLgNOK/Y9X5gr4h4R3mp1lXF914VMwNImg9cGRH/3WX/FODgiHhvf+TIvblvQxwD/LObY9mt1iLpFzR/IR/Wj3FasbjsAL1Vwed4DUnbAWcC20fEIZJ2B/YD5pSbbB2blx1gA+wcEe+s2/68pJvKCtNE5d57VDMzwMeAn0o6Eqid9I0HNgHe3l8h2vmMehiweUQ83GX/C4DHI2JFOckaK5pjuxURV/VXlnZV5edY0q+Ac4HpEbGXpMHAHyNij5KjtQ1Jvwc+FRGLiu3XAF+JiP3KTWZlkzQRGFdsLomIK/vz77fzGfXXgV8DP+my/yBgAnBcvydqIuci0UgVz06r9hx3sW1EXCTp0wAR8ayk58oO1ZWkrzc7nmsTZ+FY4PvFtWqAR4CjSszTUBXfe1XM3MU/gL8XPz/U33+8nQv1hIiY2nVnRFwg6TNlBGpG0q00fiELiIjIbQafnIetNFTB57jecknbUOSX9Gogx05O6/QJqZDHi9aKLQAi4nFJo8sO1UDl3ntUM3Otg+HPgR2BW0ifFXtI+itweDFkcuPnaOOm76URMaa3x8pSDF/pVkTc219ZekvSpsDIiLiz7CzNVPw53huYRWp+uw0YAbyr0dCRnEgaHhHLy87RCkk3RsTeXfbdUEzKkaWqvPfqVSlz0UK0Ejg5IlYX+zqAs4BNI2Jaf+Ro5wlPHpL0yq47Je0LPNzg/qWKiHtrt2LXLsXPDwH/KjFaU5LeCtxEusyApJdLurjUUN2o6nMMEBE3Aq8jTcrxb8DYnIu0pP0k3Q4sLbb3kvStkmM1JGk3Se8EtpT0jrrb0cCwkuN1q0rvvZoKZn4jcGqtSAMUP3+GfpxRrZ2bvj8FXCTpe3TurfcB4H1lheqJpA8DU4GtgZ2BFwOzgTeUmauJ04FXAr8BiIib+nMigPVRwecYSV2HCO0q6THg1ojo92tmLfhPYBJwMUBE3CzpgKaPKM/LgLcAzwfeWrf/CeDDZQRq0elU7L1H9TKvbDQEsugj8kx/hWjbQh0R10l6FfAR4Ohi9xLgVZl+sNV8lPRC/gNARNxV9FTP1bMR8ZiksnP0RtWeY0gzqO0HLCy2DwSuJRXsMyLi/LKCdSci7uvyusiu8xtARPwc+Lmk/SLi92Xn6YUqvveqlnmYpFeQrk3XEzC0v0K0baEGiIj/A06TNKLYzq7Ju4FnImJl7YVcDMPJuSPBbZKOAAZJ2gU4Abim5Ew9qdpzDLAaGFO8pmvjqr8NvIq0yEhuhfo+SfsDIWkT0utiacmZGpJ0ckScDRwhaXLX4xn3VK/ie69qmf8G1Cbpqf+MEGt7gW90bXuNWsnpkh4G7iCtNvSwpM+Vna0HVxW90jeVdBDwI+AXJWdqZhppIYNngHmknsgfKzNQC6r2HEOac/j/6rYfAnaNiH8Bq0rK1MyxpJaLHYD7gZcX2zmqfYFYTLpM1vWWqyq+9yqVOSImFnPAvxm4hJT3UdIlnUP6K0c79/r+OOnJnRoRfyn2vYR0FvLriPhamfm6U/QonAIcTPrWdhnw3WjX/1ElqOJzXHTEGkn6UgHwTlIB/BTwywouKGFWGZIuIi0qc0GxazLw/Ih4T7/8/Yw/mzaIpD8CB0XEP7rsHwEsiIhXlJOsOaX1hldEWsgeSYOAoZGWZcyOpMuBd0fEo8X2VsCFETGp1GBNVO05htRCRCrOryF9uVgE/DjXLxeSzgNO7PK6mBkRHyw1WBOSdgU+CYyi7rJgRLy+rEzNVPS9V7nMAJJujoi9etq3sbTzNeohXYs0pOvUSssF5uoKUrf/J4vtTYEFpGE5Odq29qYDiIhHKtAxq2rPMUVB/p/iVgV7NnhdZPnluM6PSL3/v0umHd+6qOJ7r4qZAf4o6dURcS1A0VH5d/31x9u5UK9cz2NlGxYRtQJCRDwp6XllBurBakkjI+KvsGZSkSzP8upU7TmuzUQ2CxhDWhBgELA8IrYoNVj3OiRtFRGPAEjamvw/b56NiG+XHaIXqvjeq2JmSJ02P6A0Ixmky1BLVcx2uLFnNcz9jbMh9pLUaHo3kfEkBqSpIvcuJrhA0j7A0yVnamY6sEhSbR7tA0hjlHNWtecY4Buk8f8/Yu18AP2yFu56mglcI+l/SB/E7wFmlBupR7+Q9BHgp6TOTgAUHfZyVMX3XhUzA7ypzD/etteoq0pp5rQLgQeLXS8C3hsN1tXOhaRtgVeTvgT9vtElh5xU9DleHBHjJd1S+/Yu6ZqIyLa5XmkpzteTXhdXRMTtJUdqStJfGuyOiHhJv4dpUdXee1DNzGVzoc5QcQ39ZaQX8h0RkePwm0qr2nMs6WrSdfXvksZv/g04ur86s5hZeVyozSqguJb3f6Tr0x8HtgS+FRHLSg3WRop+CieRFoyYWkzI8bKI+GXJ0WyAc6E2MwMk/ZA0wckHImKc0ipPv4+Il5ebrPokDW40Z7a1pm1nJrP+Jel5ksbXpmvNVTFj3Y5l5+gtSa+RdLmkP0m6u3YrO1d3JH25lX2Z2bmYSnQVQEQ8zbpzPGdH0gskjazdys7TjevKDlBlLtSZkLR3s1vZ+bqSdJikeyTdKOnNpAVPvgHcKumokuN1qxiP/LOyc6yHOaQ5hycA+9bdcnVQg339NuXielpZnEUHgKSdqev9nZviPXgX8BfgKuAe4Felhupe9l94ctbOw7OqZmaTY0HqPZuTL5Cm4NyStKLTnhFxdzF5wRXAeWWG68G1kvaNiOvLDtILj0VErh/Ca0g6jrRi3Usk1a+XvTn9OEHEejqNtE7yjpIuIM0Cd3SpiZr7Aqn39P9GxCskTSRNbZmjEZJO6u5gRHy1u2Pma9S2niT9sTYNq6RbI2KPRsdyJOl2Uo/ve4DlpG/7G33SgvVR15ryHtIkJz+h8xjfG8vI1R1JWwJbAV8CTq079ETG45HXkLQNa4cOXZvz0KG6IXs3A6+IiNWSrouIV5adrStJfyOts9DwzDoiPt+/iarFZ9QZkjQO2J26iVki4vvlJWqoo5int4M029BWrH0T5n5JJfcm2HpdW1rG1/2cXUtLRDwGPCbps8DfI+IZSQcCe0r6fv30kbmp+1L0t+LfkcUXj3sz7Qj1qKTNSMucXiDpISDHnAB/i4gzyg5RVT6jzoyk04ADSYX6UlJRWRQR7yozV1eS7iGtkdzoG3LWk0QASJoA7BIR5xYd4DarrbJmG07STaQvFaNIq5NdTBrq9OYSYzUl6Vpgb+AW0ut6XPHzNsCxEbGgxHjrULG4DCnrkaTLUBdExD9LDdZA7q1suXOhzkwxd+xewB8jYi9J25GWYHxrydHaRvFlaDypcOwqaXvgRxHxmpKjdatokj2N1JksSKtnnZHjhzKApBsjYm9JJwNPR8Ss3D+sJV0IfCEilhTbu5OWEf0C8JNch2lJ2oLOq31ld4lB0tY55qqK3JsoB6KnI2I18GzxBnwIyPrstILeDhxGuj5NRDxI6uyUswuBh0lLXb6r+PmHpSZqbpWkyaQ5yWsThuS8ah3AbrUiDVBMefqKiMhyGJykf5P0f6Sz/sWkMeCLy03VmIv0hvE16vwslvR84L9Jb7wn8RjEvrYyIkJSbRjO8LIDtWDriPhC3fYXJb2trDAtOAY4FpgREX+RNBr4QcmZenKnpG+TvhQBvBf4k6ShFGOrM/NJYGzOHd6sb7jpO2OSRgFbRMQtPd3XWifpk8AupLG+XwI+CMyLiFmlBmtC0ldIZ0sXFbveRfqQPq28VO2lGEP9EdLlBZEuL3yLdB34efVLo+ZA0q+Bd0TEU2VnsY3LhToTknaLiDu6m9wkt2E4AJI6gFsiYlzZWVohaWhEPFP8fBBpHLiAyyLi8lLD9UDSE8BwUgc+SJetlhc/R27rUhfzZH+JdUcvZH0ZR9ImpKF7AdyZ82Itkl4BnAv8gc5D9k4oLVQPVL111bPgpu98fAL4MI0nPsluGA5AMW7zZtUtBJ+53wN7Szo/It4PZF2c60VE7tfQuzqX1Pnta8BEUlN41rNTFcPIziONrxdp4pOjIuLqEmM18x3gSuBW1n6By13V1lXPggt1JiLiw8W/E8vO0ksvApZIuo61Z3hExGHlRerWJsX0pvtLekfXgxHxkxIytUzSYcABxeZvMl/VadOIuEKSIuJe4HRJvyUV71zNBA6OiDsBJO0KzAf2KTVV956NiG5n+8pVRCyTNCgingPOlXRN2Zly50KdiUaFo17GRaRKMwodSxpv+nyg63C3IM36lSVJZ5Hm9r6g2HWipAkRcWqTh5VpRXFp5C5JxwMPAC8oOVNPhtSKNEBE/Elp3fJcLZQ0FfgFnZu+c+5h/VRxeeEmSWeTJpepQmfOUvkadSYkndvkcETEB/stTJuS9O6I+JGkqRFxTtl5eqOYN/vlxdA9JA0ijbXPbtpTAEn7AktJX4q+QJqM4+yIuLbMXM0U78HVwPnFriOBwRFxTHmpuiep0QQ9WU82pMbrqn8zIv5carDMuVDbBqlS55C6SThujIjsViRrpijUB9bOliRtTWr+zrJQV1ExDOujrO31fTXwrVoHRNtwkk6MiP/qaZ915kKdmWImsjOB7SPikGJ2pP0iYk7J0RqStJh1O4fsEhGfKTVYA5IuJ13ueTnw267HM72uDoCk9wFfJq1UJtK16k9HxIVNH9jPJF3c7Hiuz3HVRjBAaiECfh0RTxRzq+9NmlntjyVH61ajL8m5z1iXA1+jzs/3SD1mpxfbfyLNQJVloYZKdQ45lPRhdj7NlxXNSlFEVpNWddqXVKhPiYi/lxqssf2A+0idsP5A5j29ayo4ggHg34tLOROAScBXgNnAq8qNta5ilrojgNFdvsxtDmQ5DW5OXKjzs21EXCTp0wAR8ayk58oO1URlOodExErSWtT7R8TDxRStERFPlJ2tmaKIHB8RF5EWt8jZC0kTydQ+mC8B5tdPzZmxKo1gAKh9LhwKfDsifi7p9BLzNHMN6bNhWzp/SX6CNAWqNeFCnZ/lxQIMtektXw08Vm6kpt5Pui59PKlzyI6k+ahztpOkK0nf5iXpUeCDEXFDubGauryYUe2HdC4iWfXwLVpVfg38urjmOxn4jaQzcp75rVClEQwAD0j6DvBG4MvF853l+g3FEL17SS0u1ku+Rp2ZYmayWaQl9m4DRgDv8jSifafomPXRiPhtsT2B1Gko245ZVerhWxSMQ0lFehSpFWBuRDxQZq5WSHoh8ErSF+XrM728AICk5wFvAm6NiLskvQjYIzJbjhPWzKzXqNiIDGfWy40LdYYkDSZNYygyncZQaTnObl88mRe930WXJS0b7bPek3Qe6Uvmr4ALI+K2kiO1TNKHgM+RZvsS8DrSUqJzSw3WA0kvoPM0rVW5xm4tcqHOkKT9SWci9WvMfr+0QA0U4yG7VTR1ZUnS14DnkTo8BWmVpEeAH0O286p/FLggIh4ttrcCJkfEt0oN1oWk1dTNQV5/iMzPnCTdCewfxRrfxSWoayLiZeUma6yYqW4msD1pOdyRwB0RMbbUYD0oWrB2iYhzJW0LbB4RjVqMrOBCnRlJ5wM7AzextrNI5DzRftVIWtjkcEREdvOqS7opIl7eZZ+HtfQhSVcAhxSdDmsLdFwaEW8sN1ljkm4mrQHwvxHxCkkTSV/eppYcrVuSTiMN43xZROwqaXvgR27Nas6dyfIzHtg9KvINqsu1p02AIWQ64UlNBedTB+go5s2udTIcRHq+re88APxB0s9Jr+nDgesknQQQEV8tM1wDqyLin5I6JHVExEJJXy47VA/eDrwCuBEgIh6UVLUFZ/qdC3V+biMNcflb2UFaEV1WdZL0NlJnnGxJ+lyj/RFxRn9n6YXLgIskzSYVkWNJvaut7/y5uNX8vPg310LyqKTNSDOoXSDpIeDZkjP1ZGVEhKTaF84sh3Lmxk3fmZD0C9IH8OakmbOuo/NE+7mO5VyHpGsj4tVl5+iOpE/UbQ4D3gIszXk+9WLSk38D3kC63rsA+G4xHMoGoKLIrSC9Ho4kzZt9Qe0ae46KIYa7kMbafwn4IDCvAkP3SuVCnQlJr2t2PCKu6q8svaHOq351kJruXxcRlRkvWQwnujgiJpWdxazdSToIOJj0BeOyiKjMuvBlcaHOjKQvR8QpPe3LRZdVv54F7gH+OyIeKidR7xU9qK+LiF3KztIdSbuQzkB2p/NQnOzGUdvGVdcvpDY9a+1DPPue9bZ+XKgz082k9bfkPC65arqMAR9EmlTmjIj4RnmpmpO0CDgN+BppLe1jSO/f00oNZtaCJhOeAOAvF825M1kmJB0HfAR4STFzVs3mwO/KSdWzYoKLE7uM752Z4/VeSS+OiPtJ16RrniWtj3tIOalatmlEXFH0/L4XOF3Sb0nF2zaApFk0LyJZDY2UNIzUmfClpHmy50ZE1p3Iap1OJZ0B/J20ME7t2nqunfWy4UKdj3mk2Zy+BJxat/+J3OZz7mLPWpEGiIhHJOU6tvcKSZMi4p76nZKOAT4L/KKUVK1ZUXQou0vS8aShRC8oOVO7WFz8+xrSpYUfFtvvBnKc//08YBVpqdY3A2OBE0tN1LpJEVG/ute3Jf0BOLusQFXgQp2JiHiMtPjGZEl7Aa8tDv0WyLlQd0jaKiIeAZC0Nfm+rj5OWtzizRFxF0CxStkRpOkic/Yx0mxqJwBfIE10cVSZgdpFRJwHIOloYGJtyt5iKFx282aT5lnYA0DSHNIIkap4TtKRwIWkVozJrJ3YybqR6wfqgCXpBGAq8JNi1w8knZPx8IWZwDWS/qfYfjcwo8Q83YqISyU9A/yqGO/9IdL6zgfUvmjkKiKuL358knR92vre9qRm2NoX482KfblZM/d/sQxumVl66wjgv4obwKJinzXhzmSZKa5P7xcRy4vt4cDvc+5MJml30hmegCsi4vaSIzVVzDX8M9Iaue+JiBXlJuqepKbrT1dpfH3uiksgpwO1KWZfB5xeO+POhdL69LX51AVsCjyFe323LRfqzBQ9kvetFY+i48j1taauXEjaIiIeL5q615HjdfUuw1qGks5MniPjDzhJDwP3kRYQ+QNrh+QA+Y6vr6pimcvaNdQ/5LzMZdU1GuFijbnpOz/nkuYb/mmx/TZgTnlxujWP1Hv6BhqskgRkN76363SnFfFC0ixOk0lNhJcA8yNiSamp2oik3SLijmIteEhfjAC2l7R9jquptYlKtdmXyWfUGSo+MCaQXshXR8QfS45kGShmUJsM/Adp3Heu/RYqpegDMrWbVdWyXE2tHUj6YkR8tuwcVeBCnYnumpBrcmtKrjv7aMhnIX2nKNCHkor0KOBi0tjZB8rMZWb9w4U6E5L+wtrrpyOBR4qfnw/8NSJGl5duXVVc07mKigllxpHG2F8YEbeVHKltSRoCHAccUOz6DfCd2nAt23CSXg3MAsaQlmkdRObL4ubAhTozxdjNiyPi0mL7EOCNEfGJ5o+0diRpNWt7+K7TF8AfcH1H0ndJ66nXenm/H3guIj5UXqr2Imkx8D7gR6QFfD4AvDQippcaLHMu1JmRdENE7NNl3+KIGF9Wpka6rJq1joj4SbPjZrmRdHNE7NXTPlt/tc+y+vULJF0TEfuXnS1n7vWdn39I+izwA9IZ1P8Dclxf9q1NjgVrJ2wxq4rnJO0cEX8GkPQSPGtWX3tK0ibATZLOBv4GDC85U/Z8Rp2ZolPZaay9TnY18PncOpOZtRtJbyANj7ybdGlhJ+CYiGjWH8N6QdJOwEOkSwwfB7YEvhURy0oNljkXatsgkrak8xeLq0hDhx4rL5XZ+il62L+MVKjviIhnSo5k5kKdG0m7Ap8kDcNZc2ki117Ukn4M3EbnDjh7RUTTa9hmuXB/i/4j6S2kRWV2In2+uVNkC1yoMyPpZmA2acavNdfHIiLH5faQdFNEvLynfWa5knRuk8OR49rqVSVpGfAO4NZw8WmZO5Pl59mI+HbZIXrhaUkTImIRgKTXAE+XnMmsZRHh1cj6z33AbS7SveMz6sxIOp3U2eKnwJrrY7l2JivWzv4+qVMIpIlajoqIW8pLZdZ7krYDzgS2j4hDilXh9ouIHOfaryRJ+5Kavq+i8+fbV0sLVQEu1JkpZijrKiIiq0UuJI2MiL/WbW8BEBGPl5fKbP1J+hWp1/f0iNhL0mDgj7mtXFdlkhaQ1lS/FVhd2x8Rny8tVAW46TszuU0V2sTPgL0hdSiLiHeWG8dsg20bERdJ+jRARDxbrP1sfWfriDi47BBV01F2AEsknVz387u7HDuz/xP1qH6JuqzO9s3W03JJ21BM1VrMS+1hhn3rfyW5UPeSm74zUb+IetcF1XNcYL1ZXrMqkrQP8HXSIii3ASOAd7m/Rd+R9ARpJrJngFV4eFZL3PSdD3Xzc6PtHOwl6XFStk2Ln8FvPKuoiLhB0utYO+HJnV45q29FxOZlZ6giF+p8RDc/N9ouXUQMKjuDWV8qVnaaC8yPiEfKztOuJO3JuhM6eVKZJtz0nYmi08pyijNU4KnaIWBYRAwpK5vZQCDppcAxwHuBxaQe4As85rfvSJoL7AksYW2vb08q0wMXajOzOpI6gLcA3yYVk7nAf+U6l0GVSLo9InYvO0fVuNe3mVmhaJadCfwH8GPgXcDjwJVl5mojvy8mkrFe8DVqMzNA0g3Ao8Ac4NS6lbP+UEyNaxvuPFKx/jup53et8+me5cbKm5u+zcwASS+JiLvLztHOikU5TmLdmcnuLS1UBfiM2sws+ZekE1i3R/IJpSVqP3+NiIvLDlE1LtRmZsmlwLV0OduzPnWHpHnAL+i8KIeHZzXhQm1mlgyLiJPKDtHmNiUV6PppRANwoW7C16jNzABJHyet7PRLKrDErA0cPqM2M0tWkoZlTWftbICBF53pM5KGAVOAscCw2n5PeNKcx1GbmSUnAS+NiFERMbq4uUj3rfOBFwKTgKuAFwNPlJqoAlyozcySJaydutc2jpdGxL8DyyPiPOBQYI+SM2XPTd9mZslzwE2SFtL5GrWHZ/Wd2mpkj0oaB/ydNBzOmnChNjNLflbcbOM5R9JWwL8DFwObAZ8rN1L+3OvbzKwLSXtHxI1l5zADF2ozs3VIujEi9i47R7uR1Gic+mPADRFxUz/HqQx3JjMzW5fKDtCmxgPHAjsUt6nAgcB/Szq5xFxZ8xm1mVkXkt4WET8rO0e7kXQZ8M6IeLLY3gz4H+DtpLNqL4HZgDuTmdmAJqlRE/dfa/t9rbpPjSRNLFOzCtgpIp6W9Ew3jxnwXKjNbKCb2eRYAK/vryADwDzgWkk/L7bfCsyXNBy4vbxYeXPTt5mZ9RtJ+wATSP0AFkXE4pIjZc+F2swGNEmvj4grJb2j0XEvwWhlc9O3mQ10rwOuJDXDduUlGK10PqM2MzPLmM+ozcwASUOBd5Lmnl7z2RgRZ5SVyQxcqM3Man5OMUsWdYtymJXNTd9mZoCk2yJiXNk5zLryFKJmZsk1krw2smXHZ9RmNqBJupXUu3swsAtwN6npW0BExJ4lxjNzoTazgU3STs2OR8S9/ZXFrBEXajOzQjG/9wTSGfbvPM+35cDXqM3MAEmfA84DtgG2Bc6V9NlyU5n5jNrMDABJS4FXRMSKYntT4MaIGFNuMhvofEZtZpbcAwyr2x4K/LmcKGZr+YzazAyQ9DNgX+By0jXqg4BFwEMAEXFCaeFsQHOhNjMDJB3V7HhEnNdfWczquVCbmRUkbQLsWmzeGRGrysxjBi7UZmYASDqQ1Ov7HtJkJzsCR0XE1eWlMnOhNjMDQNINwBERcWexvSswPyL2KTeZDXTu9W1mlgypFWmAiPgTMKTEPGaAl7k0M6u5QdIc4Pxi+0jSkpdmpXLTt5kZIGko8FHSFKICrga+FRFem9pK5UJtZgOepA7gFq9HbTnyNWozG/AiYjVws6SRZWcx68rXqM3MkhcBSyRdByyv7YyIw8qLZOZCbWZW8/myA5g14kJtZpa8OSJOqd8h6cvAVSXlMQN8jdrMrOagBvsO6fcUZl34jNrMBjRJxwEfAXaWdEvdoc2Ba8pJZbaWh2eZ2YAmaUtgK+BLwKl1h56IiH+Vk8psLRdqMzOgu6FZEfHX/s5iVs+F2swMkHQrEKRZyYYBo0lLXY4tNZgNeL5GbWYGRMQe9duS9gb+raQ4Zmu417eZWQMRcSOwb9k5zHxGbWYGSDqpbrMD2Bt4uKQ4Zmu4UJuZJZvX/fwscAnw45KymK3hzmRmZnUkDY+I5T3f06x/+Bq1mRkgaT9JtwNLi+29JH2r5FhmLtRmZoX/BCYB/wSIiJuBA8oMZAYu1GZma0TEfV12PVdKELM67kxmZpbcJ2l/ICRtApxA0QxuViZ3JjMzAyRtC/wX8EbS7GQLgBMj4p+lBrMBz4XazMwsY276NrMBTdLnmhyOiPhCv4Uxa8Bn1GY2oEn6RIPdw4EpwDYRsVk/RzLrxIXazKwgaXPgRFKRvgiYGREPlZvKBjo3fZvZgCdpa+Ak4EjgPGDviHik3FRmiQu1mQ1okv4DeAdwDrBHRDxZciSzTtz0bWYDmqTVwDOkhTjqPxBF6ky2RSnBzAou1GZmZhnzFKJmZmYZc6E2MzPLmAu1mZlZxlyozczMMuZCbWZmljEXajMzs4z9f2wAbN709+QGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "adata.obs.loc[adata.obs.cell_type == 'Microglia', new_model.cell_types].plot(kind = 'box', rot = 90, figsize = [8, 4], title = 'Microglia')\n",
    "adata.obs.loc[adata.obs.cell_type == 'Macro_pDC', new_model.cell_types].plot(kind = 'box', rot = 90, figsize = [8, 4], title = 'Macro_pDC')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dying-limitation",
   "metadata": {},
   "source": [
    "Based on this model, `Microglia`, though designated as `Unassigned` by CellTypist, holds relatively higher probability scores with `Kupffer cells`, signifying a possible tissue-resident macrophage type. `Macro_pDC`, on the other hand, holds relatively higher probability scores with both `Macrophages` and `pDC`."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "blind-damages",
   "metadata": {},
   "source": [
    "## Examine expression of cell type-driving genes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "imperial-adoption",
   "metadata": {},
   "source": [
    "Each model can be examined in terms of the driving genes for each cell type. Note these genes are only dependent on the model, say, the training dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "hawaiian-former",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Any model can be inspected.\n",
    "# Here we load the previously saved model trained from 2,000 immune cells.\n",
    "model = models.Model.load(model = 'celltypist_demo_folder/model_from_immune2000.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "prompt-theory",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['DC1', 'Endothelial cells', 'Follicular B cells', 'Kupffer cells',\n",
       "       'Macrophages', 'Mast cells', 'Neutrophil-myeloid progenitor',\n",
       "       'Plasma cells', 'gamma-delta T cells', 'pDC'], dtype=object)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.cell_types"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "current-commissioner",
   "metadata": {},
   "source": [
    "Extract the top three driving genes of `Macrophages` using the [extract_top_markers](https://celltypist.readthedocs.io/en/latest/celltypist.models.Model.html#celltypist.models.Model.extract_top_markers) method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "tribal-contributor",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['EREG', 'AQP9', 'OLR1'], dtype=object)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_3_genes = model.extract_top_markers(\"Macrophages\", 3)\n",
    "top_3_genes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "double-prompt",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1614.38x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check expression of the three genes in the training set.\n",
    "sc.pl.violin(adata_2000, top_3_genes, groupby = 'cell_type', rotation = 90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "diagnostic-street",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1614.38x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Check expression of the three genes in the query set.\n",
    "# Here we use `majority_voting` from CellTypist as the cell type labels for this dataset.\n",
    "sc.pl.violin(adata_500, top_3_genes, groupby = 'majority_voting', rotation = 90)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
